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Radiomics and Deep Learning in Brain Metastases: Current Trends and Roadmap to Future Applications

  • Received : 2021.02.08
  • Accepted : 2021.05.03
  • Published : 2021.12.30

Abstract

Advances in radiomics and deep learning (DL) hold great potential to be at the forefront of precision medicine for the treatment of patients with brain metastases. Radiomics and DL can aid clinical decision-making by enabling accurate diagnosis, facilitating the identification of molecular markers, providing accurate prognoses, and monitoring treatment response. In this review, we summarize the clinical background, unmet needs, and current state of research of radiomics and DL for the treatment of brain metastases. The promises, pitfalls, and future roadmap of radiomics and DL in brain metastases are addressed as well.

Keywords

Acknowledgement

This research received funding from the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, Information and Communication Technologies & Future Planning (2020R1A2C1003886). This research was also supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2020R1I1A1A01071648). This study was financially supported by the Faculty Research Grant of Yonsei University College of Medicine (6-2020-0149).

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